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Multi-Modal Analysis of Gene Expression from Postmortem Brains and Blood Identifies Synaptic Vesicle Trafficking Genes to Be Associated with Parkinson's Disease
52 Pages Posted: 16 May 2020
More...Abstract
Objective: We aimed to identify key susceptibility gene targets in multiple datasets generated from post-mortem brains of Parkinson’s disease (PD) patients and healthy controls (HC).
Methods: We performed a multi-tiered analysis to integrate the gene expression data using multiple-gene chips from 244 human post mortem tissues. We identified hub node genes in the highly PD-related consensus module by constructing protein-protein interaction (PPI) networks. Next we validated the top four interacting genes in 238 subjects (90 sporadic PD, 125 HC and 23 Parkinson’s Plus Syndrome (PPS)). Utilizing multinomial logistic regression analysis(MLRA) and Receiver Operating Characteristic(ROC), we analyzed the risk factors and diagnostic power for discriminating PD from HC and PPS.
Results: We identified 1333 genes that were significantly different between PD and HCs based on seven microarray datasets. The identified MEturquoise module is related to synaptic vesicle trafficking (SVT) dysfunction in PD (P<0.05), and PPI analysis revealed that SVT genes PPP2CA, SYNJ1, NSF, and PPP3CB were the top four hub node genes in MEturquoise(P<0.001). The levels of these four genes in PD postmortem brains were lower than those in HC brains. We found lower blood levels of PPP2CA, SYNJ1 and NSF in PD compared with HC, and lower SYNJ1 in PD compared with PPS (P<0.05). SYNJ1 level provided an excellent accuracy for distinguishing PD from both HC and PPS subjects. MLRA suggested that SYNJ1 and PPP2CA was independent risk factors for PD.
Conclusions: This study highlights that SVT genes, especially SYNJ1, may be promising markers in discriminating PD from HCs and PPS.
Trial Registration: This study was registered as a clinical trial (NCT: 03848455)
Funding Statement: This study was supported by the National Natural Science Foundation of China (Grant NO: 81873777), National Key R&D Program of China (Grant No: 2017YFC1310200), Natural Science Foundations of Guangdong of China (Grant NO: 2017A030311010), Leading Talent in Talents Project Guangdong High-level Personnel of Special Support Program, and Scientific Research Foundation of Guangzhou (Grant NO: 201704030080) to Q.W.; and National Natural Science Foundation of China (Grant NO: 81873776) to XYG; and National Medical Research Council (EK-T, LL-C, YX-C).
Declaration of Interests: The authors declare that they have no competing interests.
Ethics Approval Statement: Ethical approval was obtained from the ethics committee of Zhujiang Hospital of Southern Medical University (Human Ethics Number: 2018-SJNK-008).
Keywords: Genes; Parkinson's disease; weighted correlation network analysis, functional enrichment analysis, SYNJ1, PPP2CA, Parkinson-plus syndromes
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